The present disclosure is generally related to audio visualization methods for visual pattern recognition of sound. In particular, the present disclosure is directed to plotting amplitude intensity as brightness/saturation and phase-cycles as hue-variations to create visual representations of sound.
While traditional audio visualization methods depict amplitude intensities vs. time, such as in a time-frequency spectrogram, and while some may use complex phase information to augment the amplitude representation, such as in a reassigned spectrogram, the phase data are not generally represented in their own right. By plotting amplitude intensity as brightness/saturation and phase-cycles as hue-variations, the complex spectrogram method described herein displays both amplitude and phase information simultaneously, making the resulting images canonical visual representations of the source wave.
As disclosed herein, encoding log-amplitude visualization of complex-number amplitude and phase (over a wide range of intensities) into a single pixel allows for visualization of total sound. That is, visualization is provided for the total sound coming into a microphone such that every pressure front in time as it impacted the microphone's transducer is reconstructed from the resulting image. As a result, in some embodiments, the original sound is precisely reconstructed (down to the original phases) from an image, by reversing this process. This allows humans to apply their highly-developed visual pattern recognition skills to complete audio data in a new way. Applications of these methods, for example, include making “visual field guides” to sounds, as well as online image generation for sound visualization through mobile devices running browsers (e.g., in real-time and/or “without tiling of time-slices”).